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[FreeCourseSite.com] Udemy - Manage Finance Data with Python & Pandas Unique Masterclass
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[FreeCourseSite.com] Udemy - Manage Finance Data with Python & Pandas Unique Masterclass
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文件列表
19. Appendix 1 Python Crash Course (optional)/7. Data Types Lists (Part 2).mp4
140.9 MB
19. Appendix 1 Python Crash Course (optional)/17. Visualization with Matplotlib.mp4
130.3 MB
8. Time Series Data in Pandas Introduction/5. Creating a customized DatetimeIndex with pd.date_range().mp4
120.3 MB
3. Pandas Basics/5. Coding Exercise 0 Coding the Video Lectures.mp4
118.9 MB
5. Data Visualization with Matplotlib and Seaborn/3. Customization of Plots.mp4
108.1 MB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/21. Coding Exercise 13 (Solution).mp4
101.3 MB
3. Pandas Basics/17. Slicing Rows and Columns with loc (label-based indexing).mp4
95.9 MB
12. Create, Analyze and Optimize Financial Portfolios/12. Coding Exercise 15 (Solution).mp4
92.8 MB
6. Pandas Advanced Topics/8. Adding new Rows to a DataFrame.mp4
92.3 MB
13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/4. The Portfolio Diversification Effect.mp4
90.7 MB
1. Getting Started/5. Installation of Anaconda.mp4
90.4 MB
19. Appendix 1 Python Crash Course (optional)/10. Conditional Statements (if, elif, else, while).mp4
90.2 MB
8. Time Series Data in Pandas Introduction/9. Downsampling Time Series with resample() (Part 1).mp4
89.7 MB
5. Data Visualization with Matplotlib and Seaborn/8. Categorical Seaborn Plots.mp4
89.3 MB
20. Appendix 2 Numpy Crash Course (optional)/11. Visualization and (Linear) Regression.mp4
88.6 MB
4. Pandas Intermediate Topics/35. Coding Exercise 6 (Solution).mp4
88.0 MB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/2. Importing Financial Data from Excel.mp4
84.6 MB
5. Data Visualization with Matplotlib and Seaborn/9. Seaborn Regression Plots.mp4
83.3 MB
6. Pandas Advanced Topics/18. stack() and unstack().mp4
82.6 MB
17. ---------- PART 4 ADVANCED TOPICS ----------------/2. Filling NA Values with bfill, ffill and interpolation.mp4
82.3 MB
19. Appendix 1 Python Crash Course (optional)/5. Data Types Strings.mp4
81.5 MB
4. Pandas Intermediate Topics/5. EXCURSUS Updating Pandas Anaconda.mp4
80.8 MB
4. Pandas Intermediate Topics/13. Changing Row Index with set_index() and reset_index().mp4
78.7 MB
20. Appendix 2 Numpy Crash Course (optional)/5. Numpy Arrays Indexing and Slicing of multi-dimensional Arrays.mp4
77.2 MB
13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/5. Systematic vs. unsystematic Risk.mp4
76.6 MB
4. Pandas Intermediate Topics/3. Analyzing Numerical Series with unique(), nunique() and value_counts().mp4
76.2 MB
12. Create, Analyze and Optimize Financial Portfolios/4. Creating many random Portfolios with Python.mp4
76.0 MB
4. Pandas Intermediate Topics/28. Coding Exercise 5 (Solution).mp4
75.4 MB
9. Financial Data - Essential Workflows (Risk, Return & Correlation)/3. Importing Stock Price Data from Yahoo Finance (it still works!).mp4
75.3 MB
1. Getting Started/1. Course Overview and how to maximize your learning success.mp4
74.4 MB
6. Pandas Advanced Topics/16. split-apply-combine applied.mp4
74.1 MB
5. Data Visualization with Matplotlib and Seaborn/2. Visualization with Matplotlib (Intro).mp4
73.7 MB
11. Create and Analyze Financial Indexes/17. Coding Exercise 14 (Solution).mp4
73.3 MB
4. Pandas Intermediate Topics/30. Handling NA Values missing Values.mp4
71.9 MB
13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/14. Coding Exercise 16 (Solution).mp4
71.8 MB
20. Appendix 2 Numpy Crash Course (optional)/7. Generating Random Numbers.mp4
70.8 MB
1. Getting Started/7. How to use Jupyter Notebooks.mp4
69.5 MB
4. Pandas Intermediate Topics/24. Advanced Filtering with between(), isin() and ~.mp4
68.6 MB
1. Getting Started/6. Opening a Jupyter Notebook.mp4
68.2 MB
20. Appendix 2 Numpy Crash Course (optional)/2. Numpy Arrays Vectorization.mp4
67.9 MB
19. Appendix 1 Python Crash Course (optional)/14. User Defined Functions (Part 1).mp4
67.5 MB
11. Create and Analyze Financial Indexes/1. Financial Indexes - an Overview.mp4
67.5 MB
6. Pandas Advanced Topics/5. Arithmetic Operations (Part 1).mp4
66.6 MB
19. Appendix 1 Python Crash Course (optional)/6. Data Types Lists (Part 1).mp4
65.8 MB
5. Data Visualization with Matplotlib and Seaborn/12. Coding Exercise 7 (Solution).mp4
65.2 MB
3. Pandas Basics/19. Summary and Outlook.mp4
65.1 MB
14. Forward-looking Mean-Variance Optimization & Asset Allocation/2. Mean-Variance Optimization (MVO).mp4
64.7 MB
3. Pandas Basics/9. Explore your own Dataset Coding Exercise 1 (Intro).mp4
63.5 MB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/11. The S&P 500 Return Triangle (Part 2).mp4
63.3 MB
14. Forward-looking Mean-Variance Optimization & Asset Allocation/5. It´s not that simple - Part 2 (Investments 101 vs. Real World).mp4
63.0 MB
19. Appendix 1 Python Crash Course (optional)/9. Operators & Booleans.mp4
62.4 MB
16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/9. Financial Analyst Challenge (Solution Part 7).mp4
61.4 MB
6. Pandas Advanced Topics/6. Arithmetic Operations (Part 2).mp4
61.3 MB
19. Appendix 1 Python Crash Course (optional)/11. For Loops.mp4
61.2 MB
8. Time Series Data in Pandas Introduction/2. Converting strings to datetime objects with pd.to_datetime().mp4
60.8 MB
4. Pandas Intermediate Topics/32. Summary Statistics and Accumulations.mp4
60.4 MB
19. Appendix 1 Python Crash Course (optional)/15. User Defined Functions (Part 2).mp4
60.2 MB
3. Pandas Basics/4. First Steps (Inspection of Data, Part 2).mp4
59.5 MB
16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/4. Financial Analyst Challenge (Solution Part 2).mp4
59.3 MB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/10. The S&P 500 Return Triangle (Part 1).mp4
59.1 MB
9. Financial Data - Essential Workflows (Risk, Return & Correlation)/13. Coding Exercise 12 (Solution).mp4
58.7 MB
15. Interactive Financial Charts with Plotly and Cufflinks/3. Creating Offline Graphs in Jupyter Notebooks.mp4
58.1 MB
6. Pandas Advanced Topics/11. Coding Exercise 8 (Solution).mp4
57.2 MB
4. Pandas Intermediate Topics/19. Sorting DataFrames with sort_index() and sort_values().mp4
57.0 MB
12. Create, Analyze and Optimize Financial Portfolios/3. Creating the equally-weighted Portfolio.mp4
56.9 MB
3. Pandas Basics/7. Make it easy TAB Completion and Tooltip.mp4
56.8 MB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/6. S&P 500 Performance Reporting - rolling risk and return.mp4
56.7 MB
3. Pandas Basics/13. Selecting Rows with iloc (position-based indexing).mp4
56.6 MB
9. Financial Data - Essential Workflows (Risk, Return & Correlation)/9. Financial Time Series - Return and Risk.mp4
56.3 MB
20. Appendix 2 Numpy Crash Course (optional)/3. Numpy Arrays Indexing and Slicing.mp4
56.1 MB
4. Pandas Intermediate Topics/21. Filtering DataFrames (one Condition).mp4
55.5 MB
16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/8. Financial Analyst Challenge (Solution Part 6).mp4
54.9 MB
19. Appendix 1 Python Crash Course (optional)/16. User Defined Functions (Part 3).mp4
54.7 MB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/7. S&P 500 Investment Horizon and Performance.mp4
53.5 MB
3. Pandas Basics/6. Built-in Functions, Attributes and Methods.mp4
53.1 MB
3. Pandas Basics/22. Coding Exercise 2 (Solution).mp4
53.0 MB
14. Forward-looking Mean-Variance Optimization & Asset Allocation/3. It´s not that simple - Part 1 (Investments 101 vs. Real World).mp4
52.9 MB
8. Time Series Data in Pandas Introduction/12. Advanced Indexing with reindex().mp4
52.9 MB
11. Create and Analyze Financial Indexes/6. Creating a Price-Weighted Stock Index with Python.mp4
52.7 MB
20. Appendix 2 Numpy Crash Course (optional)/8. Performance Issues.mp4
52.3 MB
11. Create and Analyze Financial Indexes/12. Creating a Market Value-Weighted Stock Index with Python (Part 1).mp4
52.2 MB
6. Pandas Advanced Topics/14. Splitting with many Keys.mp4
52.1 MB
6. Pandas Advanced Topics/3. Removing Rows.mp4
52.1 MB
17. ---------- PART 4 ADVANCED TOPICS ----------------/5. Upsampling with resample().mp4
52.0 MB
19. Appendix 1 Python Crash Course (optional)/4. Data Types Integers & Floats.mp4
51.9 MB
8. Time Series Data in Pandas Introduction/10. Downsampling Time Series with resample (Part 2).mp4
51.5 MB
13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/7. Capital Asset Pricing Model (CAPM) & Security Market Line (SLM).mp4
50.7 MB
8. Time Series Data in Pandas Introduction/4. Indexing and Slicing Time Series.mp4
50.5 MB
12. Create, Analyze and Optimize Financial Portfolios/8. Finding the Optimal Portfolio.mp4
50.1 MB
16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/5. Financial Analyst Challenge (Solution Part 3).mp4
50.0 MB
6. Pandas Advanced Topics/15. split-apply-combine.mp4
49.3 MB
15. Interactive Financial Charts with Plotly and Cufflinks/5. Customizing Plotly Charts.mp4
49.2 MB
17. ---------- PART 4 ADVANCED TOPICS ----------------/3. resample() and agg().mp4
48.9 MB
6. Pandas Advanced Topics/13. Understanding the GroupBy Object.mp4
48.5 MB
13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/10. Redefining the Market Portfolio.mp4
48.0 MB
4. Pandas Intermediate Topics/29. Intro to NA Values missing Values.mp4
47.9 MB
20. Appendix 2 Numpy Crash Course (optional)/9. Case Study Numpy vs. Python Standard Library.mp4
47.8 MB
11. Create and Analyze Financial Indexes/9. Creating an Equal-Weighted Stock Index with Python.mp4
47.7 MB
20. Appendix 2 Numpy Crash Course (optional)/13. Numpy Quiz Solution.mp4
47.7 MB
3. Pandas Basics/3. First Steps (Inspection of Data, Part 1).mp4
47.4 MB
12. Create, Analyze and Optimize Financial Portfolios/6. Portfolio Analysis and the Sharpe Ratio with Python.mp4
47.0 MB
20. Appendix 2 Numpy Crash Course (optional)/10. Summary Statistics.mp4
47.0 MB
8. Time Series Data in Pandas Introduction/8. Coding Exercise 10 (Solution).mp4
46.6 MB
6. Pandas Advanced Topics/21. Coding Exercise 9 (Solution).mp4
46.6 MB
17. ---------- PART 4 ADVANCED TOPICS ----------------/1. Helpful DatetimeIndex Attributes and Methods.mp4
46.4 MB
11. Create and Analyze Financial Indexes/13. Creating a Market Value-Weighted Stock Index with Python (Part 2).mp4
46.4 MB
9. Financial Data - Essential Workflows (Risk, Return & Correlation)/5. Normalizing Time Series to a Base Value (100).mp4
46.4 MB
20. Appendix 2 Numpy Crash Course (optional)/6. Numpy Arrays Boolean Indexing.mp4
46.3 MB
8. Time Series Data in Pandas Introduction/14. Coding Exercise 11 (Solution).mp4
46.2 MB
9. Financial Data - Essential Workflows (Risk, Return & Correlation)/8. Measuring Stock Performance with MEAN Returns and STD of Returns.mp4
46.1 MB
1. Getting Started/2. Tips How to get the most out of this Course.mp4
45.8 MB
4. Pandas Intermediate Topics/12. First Steps with Pandas Index Objects.mp4
45.1 MB
14. Forward-looking Mean-Variance Optimization & Asset Allocation/4. Changing Expected Returns.mp4
45.0 MB
4. Pandas Intermediate Topics/6. Analyzing non-numerical Series with unique(), nunique(), value_counts().mp4
45.0 MB
17. ---------- PART 4 ADVANCED TOPICS ----------------/10. The Timedelta Object.mp4
44.9 MB
11. Create and Analyze Financial Indexes/10. Market Value-Weighted Index - Theory.mp4
44.8 MB
5. Data Visualization with Matplotlib and Seaborn/10. Seaborn Heatmaps.mp4
44.8 MB
13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/9. Beta and Alpha.mp4
44.7 MB
15. Interactive Financial Charts with Plotly and Cufflinks/8. SMA and Bollinger Bands with Plotly.mp4
44.7 MB
9. Financial Data - Essential Workflows (Risk, Return & Correlation)/4. Initial Inspection and Visualization.mp4
44.4 MB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/14. The S&P 500 Weather Radar.mp4
43.9 MB
19. Appendix 1 Python Crash Course (optional)/8. Data Types Tuples.mp4
43.8 MB
8. Time Series Data in Pandas Introduction/1. Importing Time Series Data from csv-files.mp4
43.8 MB
4. Pandas Intermediate Topics/8. Sorting of Series and Introduction to the inplace - parameter.mp4
43.4 MB
20. Appendix 2 Numpy Crash Course (optional)/1. Introduction to Numpy Arrays.mp4
43.1 MB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/3. Simple Moving Averages (SMA) with rolling().mp4
43.0 MB
13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/11. Cyclical vs. non-cyclical Stocks - another Intuition on Beta.mp4
42.5 MB
9. Financial Data - Essential Workflows (Risk, Return & Correlation)/7. The methods diff() and pct_change().mp4
42.2 MB
11. Create and Analyze Financial Indexes/15. Price Index vs. PerformanceTotal Return Index.mp4
41.4 MB
3. Pandas Basics/10. Explore your own Dataset Coding Exercise 1 (Solution).mp4
41.4 MB
16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/6. Financial Analyst Challenge (Solution Part 4).mp4
40.7 MB
8. Time Series Data in Pandas Introduction/11. The PeriodIndex object.mp4
40.7 MB
15. Interactive Financial Charts with Plotly and Cufflinks/4. Interactive Price Charts with Plotly.mp4
40.6 MB
3. Pandas Basics/11. Selecting Columns.mp4
40.4 MB
19. Appendix 1 Python Crash Course (optional)/19. Quiz Solution.mp4
40.1 MB
19. Appendix 1 Python Crash Course (optional)/13. Generating Random Numbers.mp4
40.0 MB
17. ---------- PART 4 ADVANCED TOPICS ----------------/7. Timezones and Converting (Part 2).mp4
38.7 MB
19. Appendix 1 Python Crash Course (optional)/12. Key words break, pass, continue.mp4
38.5 MB
5. Data Visualization with Matplotlib and Seaborn/6. Scatterplots.mp4
37.9 MB
6. Pandas Advanced Topics/2. Removing Columns.mp4
37.8 MB
4. Pandas Intermediate Topics/2. First Steps with Pandas Series.mp4
37.7 MB
4. Pandas Intermediate Topics/11. Coding Exercise 3 (Solution).mp4
37.6 MB
9. Financial Data - Essential Workflows (Risk, Return & Correlation)/6. The shift() method.mp4
37.5 MB
20. Appendix 2 Numpy Crash Course (optional)/4. Numpy Arrays Shape and Dimensions.mp4
37.3 MB
16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/7. Financial Analyst Challenge (Solution Part 5).mp4
37.2 MB
8. Time Series Data in Pandas Introduction/3. Initial Analysis Visualization of Time Series.mp4
36.7 MB
11. Create and Analyze Financial Indexes/4. Price-Weighted Index - Theory.mp4
36.7 MB
19. Appendix 1 Python Crash Course (optional)/2. First Steps.mp4
35.9 MB
5. Data Visualization with Matplotlib and Seaborn/5. Histogramms (Part 2).mp4
35.8 MB
4. Pandas Intermediate Topics/15. Renaming Index & Column Labels with rename().mp4
35.2 MB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/18. rollling() with fixed-sized time offsets.mp4
34.6 MB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/4. Momentum Trading Strategies with SMAs.mp4
34.6 MB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/13. The S&P 500 Dollar Triangle.mp4
34.5 MB
6. Pandas Advanced Topics/17. Hierarchical Indexing with Groupby.mp4
34.5 MB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/8. Simple Returns vs. Log Returns.mp4
34.2 MB
4. Pandas Intermediate Topics/20. nunique() and nlargest() nsmallest() with DataFrames.mp4
34.2 MB
11. Create and Analyze Financial Indexes/14. Comparison of weighting methods.mp4
34.1 MB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/17. Rolling Correlation.mp4
33.8 MB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/1. Intro.mp4
33.7 MB
16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/2. Financial Analyst Challenge (Instruction & Hints).mp4
33.1 MB
19. Appendix 1 Python Crash Course (optional)/3. Variables.mp4
33.0 MB
17. ---------- PART 4 ADVANCED TOPICS ----------------/8. Shifting Dates with pd.DateOffset().mp4
32.9 MB
6. Pandas Advanced Topics/9. Manipulating Elements in a DataFrame.mp4
32.8 MB
4. Pandas Intermediate Topics/23. Filtering DataFrames by many Conditions (OR).mp4
32.3 MB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/19. Merging Aligning Financial Time Series (hands-on).mp4
32.2 MB
15. Interactive Financial Charts with Plotly and Cufflinks/6. Interactive Histograms with Plotly.mp4
32.1 MB
3. Pandas Basics/16. Selecting Rows with loc (label-based indexing).mp4
31.8 MB
17. ---------- PART 4 ADVANCED TOPICS ----------------/6. Timezones and Converting (Part 1).mp4
30.7 MB
11. Create and Analyze Financial Indexes/3. Getting the Data.mp4
29.4 MB
3. Pandas Basics/1. Intro to Tabular Data Pandas.mp4
28.9 MB
4. Pandas Intermediate Topics/18. Coding Exercise 4 (Solution).mp4
28.7 MB
1. Getting Started/3. Did you know that....mp4
28.2 MB
17. ---------- PART 4 ADVANCED TOPICS ----------------/9. Advanced Date Shifting.mp4
27.9 MB
15. Interactive Financial Charts with Plotly and Cufflinks/7. Candle-Stick and OHLC Charts with Plotly.mp4
27.8 MB
3. Pandas Basics/14. Slicing Rows and Columns with iloc (position-based indexing).mp4
27.2 MB
4. Pandas Intermediate Topics/22. Filtering DataFrames by many Conditions (AND).mp4
27.2 MB
9. Financial Data - Essential Workflows (Risk, Return & Correlation)/11. Financial Time Series - Covariance and Correlation.mp4
27.0 MB
11. Create and Analyze Financial Indexes/7. Equal-Weighted Index - Theory.mp4
26.6 MB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/16. Expanding Windows.mp4
26.3 MB
4. Pandas Intermediate Topics/7. The copy() method.mp4
26.0 MB
5. Data Visualization with Matplotlib and Seaborn/4. Histogramms (Part 1).mp4
25.8 MB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/15. Exponentially-weighted Moving Averages (EWMA).mp4
24.9 MB
12. Create, Analyze and Optimize Financial Portfolios/9. Sharpe Ratio - visualized and explained.mp4
24.4 MB
4. Pandas Intermediate Topics/33. The agg() method.mp4
23.9 MB
12. Create, Analyze and Optimize Financial Portfolios/11. Coding Exercise 15 (Intro).mp4
23.6 MB
5. Data Visualization with Matplotlib and Seaborn/7. First Steps with Seaborn.mp4
23.2 MB
12. Create, Analyze and Optimize Financial Portfolios/1. Intro.mp4
23.2 MB
3. Pandas Basics/12. Selecting Rows with Square Brackets (not advisable).mp4
23.1 MB
9. Financial Data - Essential Workflows (Risk, Return & Correlation)/2. Getting Ready (Installing required library).mp4
22.8 MB
4. Pandas Intermediate Topics/14. Changing Column Labels.mp4
22.2 MB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/20. Coding Exercise 13 (intro).mp4
21.6 MB
14. Forward-looking Mean-Variance Optimization & Asset Allocation/1. Intro.mp4
21.5 MB
15. Interactive Financial Charts with Plotly and Cufflinks/2. Getting Ready (Installing required libraries).mp4
19.7 MB
13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/13. Coding Exercise 16 (Intro).mp4
19.7 MB
16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/3. Financial Analyst Challenge (Solution Part 1).mp4
19.2 MB
6. Pandas Advanced Topics/4. Adding new Columns to a DataFrame.mp4
18.8 MB
9. Financial Data - Essential Workflows (Risk, Return & Correlation)/12. Coding Exercise 12 (intro).mp4
18.4 MB
4. Pandas Intermediate Topics/25. any() and all().mp4
18.4 MB
12. Create, Analyze and Optimize Financial Portfolios/5. What is the Sharpe Ratio and a Risk Free Asset.mp4
17.7 MB
15. Interactive Financial Charts with Plotly and Cufflinks/1. Intro.mp4
17.3 MB
13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/2. Capital Market Line (CML) & Two-Fund-Theorem.mp4
16.6 MB
4. Pandas Intermediate Topics/34. Coding Exercise 6 (Intro).mp4
16.1 MB
4. Pandas Intermediate Topics/31. Exporting DataFrames to csv.mp4
13.9 MB
8. Time Series Data in Pandas Introduction/6. More on pd.date_range().mp4
13.0 MB
12. Create, Analyze and Optimize Financial Portfolios/2. Getting the Data.mp4
12.8 MB
11. Create and Analyze Financial Indexes/16. Coding Exercise 14 (intro).mp4
11.9 MB
15. Interactive Financial Charts with Plotly and Cufflinks/9. More Technical Indicators with Plotly (Volume, MACD, DMI).mp4
11.7 MB
4. Pandas Intermediate Topics/27. Coding Exercise 5 (Intro).mp4
11.5 MB
5. Data Visualization with Matplotlib and Seaborn/11. Coding Exercise 7 (Intro).mp4
11.2 MB
4. Pandas Intermediate Topics/10. Coding Exercise 3 (Intro).mp4
11.0 MB
6. Pandas Advanced Topics/12. Introduction to GroupBy Operations.mp4
10.5 MB
13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/1. Intro.mp4
10.5 MB
16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/1. Financial Analyst Challenge (Intro).mp4
10.5 MB
8. Time Series Data in Pandas Introduction/7. Coding Exercise 10 (intro).mp4
10.4 MB
6. Pandas Advanced Topics/10. Coding Exercise 8 (Intro).mp4
9.5 MB
17. ---------- PART 4 ADVANCED TOPICS ----------------/4. resample() and OHLC().mp4
9.2 MB
8. Time Series Data in Pandas Introduction/13. Coding Exercise 11 (intro).mp4
9.2 MB
3. Pandas Basics/21. Coding Exercise 2 (Intro).mp4
9.1 MB
6. Pandas Advanced Topics/20. Coding Exercise 9 (Intro).mp4
8.2 MB
4. Pandas Intermediate Topics/17. Coding Exercise 4 (Intro).mp4
8.0 MB
19. Appendix 1 Python Crash Course (optional)/1. Intro.mp4
6.2 MB
3. Pandas Basics/9.1 Finance_Data_Exc.zip.zip
4.5 MB
3. Pandas Basics/5.1 Video-Lecture-NBs.zip.zip
2.5 MB
16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/1.1 Final_Project.zip.zip
2.1 MB
19. Appendix 1 Python Crash Course (optional)/7. Data Types Lists (Part 2).vtt
18.6 kB
8. Time Series Data in Pandas Introduction/5. Creating a customized DatetimeIndex with pd.date_range().vtt
16.1 kB
3. Pandas Basics/5. Coding Exercise 0 Coding the Video Lectures.vtt
15.9 kB
5. Data Visualization with Matplotlib and Seaborn/8. Categorical Seaborn Plots.vtt
15.2 kB
1. Getting Started/7. How to use Jupyter Notebooks.vtt
15.2 kB
6. Pandas Advanced Topics/18. stack() and unstack().vtt
14.9 kB
19. Appendix 1 Python Crash Course (optional)/17. Visualization with Matplotlib.vtt
14.8 kB
8. Time Series Data in Pandas Introduction/9. Downsampling Time Series with resample() (Part 1).vtt
14.7 kB
20. Appendix 2 Numpy Crash Course (optional)/13. Numpy Quiz Solution.vtt
14.6 kB
6. Pandas Advanced Topics/8. Adding new Rows to a DataFrame.vtt
14.0 kB
19. Appendix 1 Python Crash Course (optional)/10. Conditional Statements (if, elif, else, while).vtt
13.8 kB
13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/4. The Portfolio Diversification Effect.vtt
13.6 kB
4. Pandas Intermediate Topics/3. Analyzing Numerical Series with unique(), nunique() and value_counts().vtt
13.2 kB
6. Pandas Advanced Topics/5. Arithmetic Operations (Part 1).vtt
13.2 kB
20. Appendix 2 Numpy Crash Course (optional)/11. Visualization and (Linear) Regression.vtt
12.9 kB
6. Pandas Advanced Topics/6. Arithmetic Operations (Part 2).vtt
12.9 kB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/6. S&P 500 Performance Reporting - rolling risk and return.vtt
12.9 kB
13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/5. Systematic vs. unsystematic Risk.vtt
12.8 kB
6. Pandas Advanced Topics/16. split-apply-combine applied.vtt
12.8 kB
19. Appendix 1 Python Crash Course (optional)/19. Quiz Solution.vtt
12.7 kB
5. Data Visualization with Matplotlib and Seaborn/9. Seaborn Regression Plots.vtt
12.5 kB
5. Data Visualization with Matplotlib and Seaborn/3. Customization of Plots.vtt
12.4 kB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/21. Coding Exercise 13 (Solution).vtt
12.4 kB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/2. Importing Financial Data from Excel.vtt
12.2 kB
12. Create, Analyze and Optimize Financial Portfolios/4. Creating many random Portfolios with Python.vtt
12.1 kB
14. Forward-looking Mean-Variance Optimization & Asset Allocation/5. It´s not that simple - Part 2 (Investments 101 vs. Real World).vtt
11.9 kB
4. Pandas Intermediate Topics/30. Handling NA Values missing Values.vtt
11.8 kB
4. Pandas Intermediate Topics/21. Filtering DataFrames (one Condition).vtt
11.4 kB
1. Getting Started/1. Course Overview and how to maximize your learning success.vtt
11.2 kB
4. Pandas Intermediate Topics/35. Coding Exercise 6 (Solution).vtt
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3. Pandas Basics/17. Slicing Rows and Columns with loc (label-based indexing).vtt
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12. Create, Analyze and Optimize Financial Portfolios/12. Coding Exercise 15 (Solution).vtt
10.8 kB
17. ---------- PART 4 ADVANCED TOPICS ----------------/2. Filling NA Values with bfill, ffill and interpolation.vtt
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10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/7. S&P 500 Investment Horizon and Performance.vtt
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4. Pandas Intermediate Topics/13. Changing Row Index with set_index() and reset_index().vtt
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6. Pandas Advanced Topics/15. split-apply-combine.vtt
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11. Create and Analyze Financial Indexes/1. Financial Indexes - an Overview.vtt
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4. Pandas Intermediate Topics/32. Summary Statistics and Accumulations.vtt
10.5 kB
3. Pandas Basics/19. Summary and Outlook.vtt
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3. Pandas Basics/7. Make it easy TAB Completion and Tooltip.vtt
10.4 kB
20. Appendix 2 Numpy Crash Course (optional)/5. Numpy Arrays Indexing and Slicing of multi-dimensional Arrays.vtt
10.2 kB
19. Appendix 1 Python Crash Course (optional)/11. For Loops.vtt
10.2 kB
19. Appendix 1 Python Crash Course (optional)/5. Data Types Strings.vtt
10.1 kB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/8. Simple Returns vs. Log Returns.vtt
10.0 kB
8. Time Series Data in Pandas Introduction/2. Converting strings to datetime objects with pd.to_datetime().vtt
9.9 kB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/11. The S&P 500 Return Triangle (Part 2).vtt
9.9 kB
19. Appendix 1 Python Crash Course (optional)/9. Operators & Booleans.vtt
9.9 kB
11. Create and Analyze Financial Indexes/6. Creating a Price-Weighted Stock Index with Python.vtt
9.8 kB
1. Getting Started/6. Opening a Jupyter Notebook.vtt
9.8 kB
11. Create and Analyze Financial Indexes/10. Market Value-Weighted Index - Theory.vtt
9.7 kB
5. Data Visualization with Matplotlib and Seaborn/2. Visualization with Matplotlib (Intro).vtt
9.7 kB
4. Pandas Intermediate Topics/19. Sorting DataFrames with sort_index() and sort_values().vtt
9.7 kB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/3. Simple Moving Averages (SMA) with rolling().vtt
9.7 kB
9. Financial Data - Essential Workflows (Risk, Return & Correlation)/8. Measuring Stock Performance with MEAN Returns and STD of Returns.vtt
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4. Pandas Intermediate Topics/29. Intro to NA Values missing Values.vtt
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4. Pandas Intermediate Topics/8. Sorting of Series and Introduction to the inplace - parameter.vtt
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19. Appendix 1 Python Crash Course (optional)/14. User Defined Functions (Part 1).vtt
9.4 kB
11. Create and Analyze Financial Indexes/4. Price-Weighted Index - Theory.vtt
9.4 kB
14. Forward-looking Mean-Variance Optimization & Asset Allocation/2. Mean-Variance Optimization (MVO).vtt
9.3 kB
13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/14. Coding Exercise 16 (Solution).vtt
9.3 kB
5. Data Visualization with Matplotlib and Seaborn/10. Seaborn Heatmaps.vtt
9.3 kB
8. Time Series Data in Pandas Introduction/12. Advanced Indexing with reindex().vtt
9.2 kB
8. Time Series Data in Pandas Introduction/10. Downsampling Time Series with resample (Part 2).vtt
9.0 kB
9. Financial Data - Essential Workflows (Risk, Return & Correlation)/3. Importing Stock Price Data from Yahoo Finance (it still works!).vtt
9.0 kB
9. Financial Data - Essential Workflows (Risk, Return & Correlation)/9. Financial Time Series - Return and Risk.vtt
9.0 kB
20. Appendix 2 Numpy Crash Course (optional)/7. Generating Random Numbers.vtt
9.0 kB
19. Appendix 1 Python Crash Course (optional)/2. First Steps.vtt
9.0 kB
3. Pandas Basics/6. Built-in Functions, Attributes and Methods.vtt
8.9 kB
20. Appendix 2 Numpy Crash Course (optional)/2. Numpy Arrays Vectorization.vtt
8.9 kB
12. Create, Analyze and Optimize Financial Portfolios/3. Creating the equally-weighted Portfolio.vtt
8.9 kB
11. Create and Analyze Financial Indexes/12. Creating a Market Value-Weighted Stock Index with Python (Part 1).vtt
8.9 kB
3. Pandas Basics/4. First Steps (Inspection of Data, Part 2).vtt
8.9 kB
11. Create and Analyze Financial Indexes/9. Creating an Equal-Weighted Stock Index with Python.vtt
8.8 kB
6. Pandas Advanced Topics/13. Understanding the GroupBy Object.vtt
8.8 kB
19. Appendix 1 Python Crash Course (optional)/6. Data Types Lists (Part 1).vtt
8.7 kB
8. Time Series Data in Pandas Introduction/1. Importing Time Series Data from csv-files.vtt
8.7 kB
4. Pandas Intermediate Topics/28. Coding Exercise 5 (Solution).vtt
8.6 kB
3. Pandas Basics/9. Explore your own Dataset Coding Exercise 1 (Intro).vtt
8.6 kB
17. ---------- PART 4 ADVANCED TOPICS ----------------/10. The Timedelta Object.vtt
8.4 kB
4. Pandas Intermediate Topics/24. Advanced Filtering with between(), isin() and ~.vtt
8.1 kB
9. Financial Data - Essential Workflows (Risk, Return & Correlation)/13. Coding Exercise 12 (Solution).vtt
8.1 kB
11. Create and Analyze Financial Indexes/17. Coding Exercise 14 (Solution).vtt
8.1 kB
3. Pandas Basics/11. Selecting Columns.vtt
8.0 kB
20. Appendix 2 Numpy Crash Course (optional)/1. Introduction to Numpy Arrays.vtt
8.0 kB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/17. Rolling Correlation.vtt
8.0 kB
1. Getting Started/5. Installation of Anaconda.vtt
8.0 kB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/4. Momentum Trading Strategies with SMAs.vtt
7.9 kB
13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/9. Beta and Alpha.vtt
7.9 kB
16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/8. Financial Analyst Challenge (Solution Part 6).vtt
7.8 kB
13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/7. Capital Asset Pricing Model (CAPM) & Security Market Line (SLM).vtt
7.8 kB
11. Create and Analyze Financial Indexes/13. Creating a Market Value-Weighted Stock Index with Python (Part 2).vtt
7.8 kB
13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/10. Redefining the Market Portfolio.vtt
7.8 kB
19. Appendix 1 Python Crash Course (optional)/4. Data Types Integers & Floats.vtt
7.8 kB
16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/9. Financial Analyst Challenge (Solution Part 7).vtt
7.7 kB
20. Appendix 2 Numpy Crash Course (optional)/9. Case Study Numpy vs. Python Standard Library.vtt
7.7 kB
4. Pandas Intermediate Topics/6. Analyzing non-numerical Series with unique(), nunique(), value_counts().vtt
7.7 kB
9. Financial Data - Essential Workflows (Risk, Return & Correlation)/6. The shift() method.vtt
7.7 kB
20. Appendix 2 Numpy Crash Course (optional)/10. Summary Statistics.vtt
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8. Time Series Data in Pandas Introduction/4. Indexing and Slicing Time Series.vtt
7.6 kB
16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/4. Financial Analyst Challenge (Solution Part 2).vtt
7.6 kB
3. Pandas Basics/13. Selecting Rows with iloc (position-based indexing).vtt
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9. Financial Data - Essential Workflows (Risk, Return & Correlation)/7. The methods diff() and pct_change().vtt
7.6 kB
12. Create, Analyze and Optimize Financial Portfolios/8. Finding the Optimal Portfolio.vtt
7.5 kB
5. Data Visualization with Matplotlib and Seaborn/12. Coding Exercise 7 (Solution).vtt
7.5 kB
12. Create, Analyze and Optimize Financial Portfolios/6. Portfolio Analysis and the Sharpe Ratio with Python.vtt
7.5 kB
6. Pandas Advanced Topics/3. Removing Rows.vtt
7.4 kB
5. Data Visualization with Matplotlib and Seaborn/6. Scatterplots.vtt
7.3 kB
6. Pandas Advanced Topics/14. Splitting with many Keys.vtt
7.3 kB
19. Appendix 1 Python Crash Course (optional)/3. Variables.vtt
7.3 kB
4. Pandas Intermediate Topics/2. First Steps with Pandas Series.vtt
7.2 kB
5. Data Visualization with Matplotlib and Seaborn/5. Histogramms (Part 2).vtt
7.2 kB
15. Interactive Financial Charts with Plotly and Cufflinks/3. Creating Offline Graphs in Jupyter Notebooks.vtt
7.1 kB
3. Pandas Basics/22. Coding Exercise 2 (Solution).vtt
7.0 kB
19. Appendix 1 Python Crash Course (optional)/13. Generating Random Numbers.vtt
7.0 kB
14. Forward-looking Mean-Variance Optimization & Asset Allocation/4. Changing Expected Returns.vtt
7.0 kB
19. Appendix 1 Python Crash Course (optional)/15. User Defined Functions (Part 2).vtt
6.9 kB
9. Financial Data - Essential Workflows (Risk, Return & Correlation)/5. Normalizing Time Series to a Base Value (100).vtt
6.9 kB
11. Create and Analyze Financial Indexes/15. Price Index vs. PerformanceTotal Return Index.vtt
6.9 kB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/10. The S&P 500 Return Triangle (Part 1).vtt
6.9 kB
19. Appendix 1 Python Crash Course (optional)/8. Data Types Tuples.vtt
6.9 kB
6. Pandas Advanced Topics/17. Hierarchical Indexing with Groupby.vtt
6.8 kB
14. Forward-looking Mean-Variance Optimization & Asset Allocation/3. It´s not that simple - Part 1 (Investments 101 vs. Real World).vtt
6.8 kB
10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/18. rollling() with fixed-sized time offsets.vtt
6.8 kB
13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/11. Cyclical vs. non-cyclical Stocks - another Intuition on Beta.vtt
6.8 kB
6. Pandas Advanced Topics/21. Coding Exercise 9 (Solution).vtt
6.7 kB
17. ---------- PART 4 ADVANCED TOPICS ----------------/5. Upsampling with resample().vtt
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6. Pandas Advanced Topics/11. Coding Exercise 8 (Solution).vtt
6.6 kB
19. Appendix 1 Python Crash Course (optional)/12. Key words break, pass, continue.vtt
6.5 kB
17. ---------- PART 4 ADVANCED TOPICS ----------------/1. Helpful DatetimeIndex Attributes and Methods.vtt
6.4 kB
4. Pandas Intermediate Topics/5. EXCURSUS Updating Pandas Anaconda.vtt
6.4 kB
8. Time Series Data in Pandas Introduction/11. The PeriodIndex object.vtt
6.4 kB
16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/5. Financial Analyst Challenge (Solution Part 3).vtt
6.4 kB
15. Interactive Financial Charts with Plotly and Cufflinks/8. SMA and Bollinger Bands with Plotly.vtt
6.3 kB
11. Create and Analyze Financial Indexes/7. Equal-Weighted Index - Theory.vtt
6.3 kB
20. Appendix 2 Numpy Crash Course (optional)/6. Numpy Arrays Boolean Indexing.vtt
6.3 kB
5. Data Visualization with Matplotlib and Seaborn/7. First Steps with Seaborn.vtt
6.3 kB
20. Appendix 2 Numpy Crash Course (optional)/4. Numpy Arrays Shape and Dimensions.vtt
6.2 kB
20. Appendix 2 Numpy Crash Course (optional)/8. Performance Issues.vtt
6.2 kB
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4. Pandas Intermediate Topics/12. First Steps with Pandas Index Objects.vtt
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1. Getting Started/2. Tips How to get the most out of this Course.vtt
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3. Pandas Basics/16. Selecting Rows with loc (label-based indexing).vtt
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4. Pandas Intermediate Topics/20. nunique() and nlargest() nsmallest() with DataFrames.vtt
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15. Interactive Financial Charts with Plotly and Cufflinks/6. Interactive Histograms with Plotly.vtt
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8. Time Series Data in Pandas Introduction/8. Coding Exercise 10 (Solution).vtt
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1. Getting Started/4. FAQ Important Information.html
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17. ---------- PART 4 ADVANCED TOPICS ----------------/3. resample() and agg().vtt
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14. Forward-looking Mean-Variance Optimization & Asset Allocation/1. Intro.vtt
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16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/7. Financial Analyst Challenge (Solution Part 5).vtt
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10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/15. Exponentially-weighted Moving Averages (EWMA).vtt
5.1 kB
15. Interactive Financial Charts with Plotly and Cufflinks/5. Customizing Plotly Charts.vtt
5.0 kB
9. Financial Data - Essential Workflows (Risk, Return & Correlation)/11. Financial Time Series - Covariance and Correlation.vtt
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12. Create, Analyze and Optimize Financial Portfolios/5. What is the Sharpe Ratio and a Risk Free Asset.vtt
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17. ---------- PART 4 ADVANCED TOPICS ----------------/7. Timezones and Converting (Part 2).vtt
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15. Interactive Financial Charts with Plotly and Cufflinks/4. Interactive Price Charts with Plotly.vtt
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16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/6. Financial Analyst Challenge (Solution Part 4).vtt
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17. ---------- PART 4 ADVANCED TOPICS ----------------/8. Shifting Dates with pd.DateOffset().vtt
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5. Data Visualization with Matplotlib and Seaborn/4. Histogramms (Part 1).vtt
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17. ---------- PART 4 ADVANCED TOPICS ----------------/6. Timezones and Converting (Part 1).vtt
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16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/2. Financial Analyst Challenge (Instruction & Hints).vtt
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16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/3. Financial Analyst Challenge (Solution Part 1).vtt
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9. Financial Data - Essential Workflows (Risk, Return & Correlation)/1. Intro.html
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12. Create, Analyze and Optimize Financial Portfolios/10. Portfolios.html
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12. Create, Analyze and Optimize Financial Portfolios/7. Sharpe Ratio and Risk Free Asset.html
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13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/12. Beta and Alpha.html
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13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/3. Two-Fund-Theorem.html
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13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/6. Risk Diversification.html
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13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/8. CAPM.html
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19. Appendix 1 Python Crash Course (optional)/18. Python Basics.html
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20. Appendix 2 Numpy Crash Course (optional)/12. Numpy.html
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3. Pandas Basics/20. Indexing and Slicing.html
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3. Pandas Basics/8. First Steps.html
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4. Pandas Intermediate Topics/16. Pandas Index Objects.html
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4. Pandas Intermediate Topics/26. Sorting and Filtering.html
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4. Pandas Intermediate Topics/9. Pandas Series.html
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6. Pandas Advanced Topics/19. GroupBy.html
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9. Financial Data - Essential Workflows (Risk, Return & Correlation)/10. Risk & Return.html
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0. Websites you may like/[FCS Forum].url
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0. Websites you may like/[FreeCourseSite.com].url
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0. Websites you may like/[CourseClub.ME].url
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18. ------------------ APPENDIX -------------------/1. Welcome to the Appendix.html
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21. Bonus/1. Bonus Lecture.html
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